CIS 5210 - Module 7 - Markov Decision Processes

This episode explores MDPs, covering stochastic environments, transition functions, reward functions, policies, value iteration, policy iteration, expected utility, finite vs. infinite horizons, discount factors, etc.

Disclosure: This episode was generated using NotebookLM by uploading Professor Chris Callison-Burch's lecture notes and slides.